The present invention relates to a method of improving OPC modeling.
During the optical lithography step in integrated circuit fabrication, a device structure is patterned by imaging a mask onto a radiation sensitive film (photoresist or resist) coating different thin film materials on the wafer. These photoresist films capture the pattern delineated through initial exposure to radiation and allow subsequent pattern transfer to the underlying layers. The radiation source, imaging optics, mask type and resist performance determine the minimum feature size that can be reproduced by the lithography process. Imaging of mask patterns with critical dimensions smaller than the exposure wavelength results in distorted images of the original layout pattern, primarily because of optical proximity effects of the imaging optics. Nonlinear response of the photoresist to variability in exposure tool and mask manufacturing process as well as variability in resist and thin film processes also contribute to image distortion. These distortions include variations in the line-widths of identically drawn features in dense and isolated environments (iso-dense bias), line-end pullback or line-end shortening from drawn positions and corner rounding. The process of correcting these types of distortions is called optical proximity correction or optical and process correction (OPC). OPC is a procedure of pre-distorting the mask layout by using simple shape manipulation rules (rule-based OPC) or fragmenting the original polygon into line segments and moving these segments to favorable positions as determined by a process model (model-based OPC). OPCed mask improves image fidelity on a wafer.
As the semiconductor industry pushes to resolve smaller critical dimensions, the need to provide more accurate OPC modeling becomes critical. Present techniques are either based solely on experiment and observation rather than theory, i.e., empirical, or are derived from first principals. Empirical models are generated using top down critical dimension measurements or scanning electron microscope (SEM) images.
Currently, existing OPC models do not take into account the slope of the resist while leading wafer level simulators (such as Prolith) approximate the image slope at best by correlating the slope of the resist profile, at several focus and exposure settings, to a cross-section and adjusting diffusion parameters to get the profiles-close. Because of this, first principal models are susceptible to the same inaccuracies seen in the empirical models. First principal models are inaccurate because they fail to fully grasp every aspect of lithography (diffusion, reflectivity, flare, etc.), so their functions are inaccurate. Empirical models generated from top down images or critical dimensions are inaccurate because they assume the slope from the image contrast.
Existing OPC models are disadvantageous because they are unable to accurately model the top critical dimension, the bottom critical dimension, resist loss, profile and the diffusion effects through focus, due to the limited information available in the empirical data based only on top down critical dimensions/images.
Therefore, an improved method for OPC modeling is needed. The present invention provides such a method for OPC modeling. Features and advantages of the present invention will become apparent upon a reading of the attached specification, in combination with a study of the drawings.